寒地校园植物群落对大气细颗粒物浓度的消减作用

近年来随着我国城市的快速发展,空气污染作为城市生态环境破坏的首要问题日益严重。因此探究城市绿地中的植物群落是否能够消减大气细颗粒物浓度及其变化特征成为公众和学者广泛关注的焦点。选取位于寒地城市哈尔滨的东北林业大学作为研究对象,通过对校园PM_2.5浓度进行测定和校园植物群落进行调查,定量地分析不同植物群落对PM_2.5浓度的消减作用、PM_2.5浓度的时间变化规律、PM_2.5浓度与温度和空气相对湿度之间的关系。结果显示：（1）PM_2.5浓度日变化呈"双峰单谷"型,早晚偏高;季节变化是夏季PM_2.5浓度最低,秋季PM_2.5浓度最高。（2）不同结构的植物群落对大气细颗粒物的削减效果略有差异,乔灌草配置型绿地的PM_2.5消减率为30.30%,消减效果最佳;乔草和灌草的PM_2.5消减率分别为14.30%和7.77%,消减效果较差。（3）PM_2.5浓度与温度呈负相关关系,与空气相对湿度呈正相关关系。

Reduction effects of plant community on the concentration of atmospheric fine particles in a cold zone campus

In recent years, with the rapid development of cities in China, air pollution has become increasingly serious as the primary problem of urban ecological and environmental damage. Therefore, exploring whether plant communities in urban green spaces can reduce the concentration of atmospheric fine particles and their changing characteristics has become the focus of widespread attention by the public and scholars. This paper selects Northeast Forestry University in the cold city of Harbin as the research object. By measuring the concentration of PM_2.5 and investigating the plant community on campus, the effects of different plant communities on the reduction of PM_2.5 concentration, the temporal variation of PM_2.5 concentration and the relationship between PM_2.5 concentration and temperature and air relative humidity were analyzed quantitatively. The results show that: (1) the diurnal variation of PM_2.5 concentration shows a "double peak and single valley" pattern, with higher morning and evening; the seasonal variation presents the lowest PM_2.5 concentration in summer and the highest PM_2.5 concentration in autumn. (2) Plant communities with different structures have slightly different effects on the reduction of atmospheric fine particles. The reduction rate of PM_2.5 in arbor-shrub-grass greenbelt is 30.30%, which is the best reduction effect; the reduction rate of PM_2.5 of arbor and shrub was 14.30% and 7.77%, and the reduction effect was poor. (3) PM_2.5 concentration has a negative correlation with temperature, and a positive correlation with air relative humidity.